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Machine Learning Force Fields and Coarse-Grained Variables in Molecular  Dynamics: Application to Materials and Biological Systems | Journal of  Chemical Theory and Computation
Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems | Journal of Chemical Theory and Computation

Closed-form continuous-time neural networks | Nature Machine Intelligence
Closed-form continuous-time neural networks | Nature Machine Intelligence

Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning |  Journal of Chemical Theory and Computation
Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning | Journal of Chemical Theory and Computation

Artificial neural network - Wikipedia
Artificial neural network - Wikipedia

Time series in healthcare: challenges and solutions // van der Schaar Lab
Time series in healthcare: challenges and solutions // van der Schaar Lab

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

Physics-informed neural networks - Wikipedia
Physics-informed neural networks - Wikipedia

Frontiers | Prediction of wastewater treatment system based on deep learning
Frontiers | Prediction of wastewater treatment system based on deep learning

Self-directed online machine learning for topology optimization | Nature  Communications
Self-directed online machine learning for topology optimization | Nature Communications

Embracing Change: Continual Learning in Deep Neural Networks: Trends in  Cognitive Sciences
Embracing Change: Continual Learning in Deep Neural Networks: Trends in Cognitive Sciences

LM101-081: Ch3: How to Define Machine Learning (or at Least Try) - Learning  Machines 101
LM101-081: Ch3: How to Define Machine Learning (or at Least Try) - Learning Machines 101

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

Frontiers | Generative Models of Brain Dynamics
Frontiers | Generative Models of Brain Dynamics

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

11 The system dynamics modeling process | Download Scientific Diagram
11 The system dynamics modeling process | Download Scientific Diagram

From calibration to parameter learning: Harnessing the scaling effects of  big data in geoscientific modeling | Nature Communications
From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling | Nature Communications

Time series in healthcare: challenges and solutions // van der Schaar Lab
Time series in healthcare: challenges and solutions // van der Schaar Lab

Chasing collective variables using temporal data-driven strategies | QRB  Discovery | Cambridge Core
Chasing collective variables using temporal data-driven strategies | QRB Discovery | Cambridge Core

From Computational Fluid Dynamics to Structure Interpretation via Neural  Networks: An Application to Flow and Transport in Porous Media | Industrial  & Engineering Chemistry Research
From Computational Fluid Dynamics to Structure Interpretation via Neural Networks: An Application to Flow and Transport in Porous Media | Industrial & Engineering Chemistry Research

Next generation reservoir computing | Nature Communications
Next generation reservoir computing | Nature Communications

Modeling of dynamical systems through deep learning | SpringerLink
Modeling of dynamical systems through deep learning | SpringerLink

Artificial neural network - Wikipedia
Artificial neural network - Wikipedia

Unraveling hidden interactions in complex systems with deep learning |  Scientific Reports
Unraveling hidden interactions in complex systems with deep learning | Scientific Reports

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear  Processes | Industrial & Engineering Chemistry Research
Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear Processes | Industrial & Engineering Chemistry Research

A review of dynamical systems approaches for the detection of chaotic  attractors in cancer networks - ScienceDirect
A review of dynamical systems approaches for the detection of chaotic attractors in cancer networks - ScienceDirect

Deep multi-modal learning for joint linear representation of nonlinear dynamical  systems | Scientific Reports
Deep multi-modal learning for joint linear representation of nonlinear dynamical systems | Scientific Reports